SoroushVahidi/scidocs huggingface dataset:
High Resolution AMOLED Pixel Using Negative Feedback Structure for Improving Image Quality
(2013)

Abstract An active matrix organic light emitting diode (AMOLED) pixel structure is proposed to improve image quality of high resolution small sized displays. The proposed pixel structure increases luminance uniformity by decreasing the distortion of the voltage in the storage capacitors using negative feedback structure. The simulation results show that the distortion of the voltage in the storage capacitors with negative feedback structure decreases to 55.3% compared to that without negative feedback structure and the emission current error of the proposed pixel structure ranges from –0.71 LSB to 0.56 LSB when the threshold voltage of the driving TFT varies from –0.2 V to 0.2 V.
Interactive Spatial Augmented Reality in Collaborative Robot Programming: User Experience Evaluation
(2018)

This paper presents a novel approach to interaction between human workers and industrial collaborative robots. The proposed approach addresses problems introduced by existing solutions for robot programming. It aims to reduce the mental demands and attention switches by centering all interaction in a shared workspace, combining various modalities and enabling interaction with the system without any external devices. The concept allows simple programming in the form of setting program parameters using spatial augmented reality for visualization and a touch-enabled table and robotic arms as input devices. We evaluated the concept utilizing a user experience study with six participants (shop-floor workers). All participants were able to program the robot and to collaborate with it using the program they parametrized. The final goal is to create a distraction-free, usable and low-effort interface for effective human-robot collaboration, enabling any ordinary skilled worker to customize the robot's program to changes in production or to personal (e.g. ergonomic) needs.
Accurate Scale Estimation for Robust Visual Tracking
(2014)

Robust scale estimation is a challenging problem in visual object tracking. Most existing methods fail to handle large scale variations in complex image sequences. This paper presents a novel approach for robust scale estimation in a tracking-by-detection framework. The proposed approach works by learning discriminative correlation filters based on a scale pyramid representation. We learn separate filters for translation and scale estimation, and show that this improves the performance compared to an exhaustive scale search. Our scale estimation approach is generic as it can be incorporated into any tracking method with no inherent scale estimation. Experiments are performed on 28 benchmark sequences with significant scale variations. Our results show that the proposed approach significantly improves the performance by 18.8% in median distance precision compared to our baseline. Finally, we provide both quantitative and qualitative comparison of our approach with state-of-theart trackers in literature. The proposed method is shown to outperform the best existing tracker by 16.6% in median distance precision, while operating at real-time.
ClaimVerif: A Real-time Claim Verification System Using the Web and Fact Databases
(2017)

Our society is increasingly digitalized. Every day, a tremendous amount of information is being created, shared, and digested through all kinds of cyber channels. Although people can easily acquire information from various sources (social media, news articles, etc.), the truthfulness of most received information remains unverified. In many real-life scenarios, false information has become the de facto cause that leads to detrimental decision makings, and techniques that can automatically filter false information are highly demanded. However, verifying whether a piece of information is trustworthy is difficult because: (1) selecting candidate snippets for fact checking is nontrivial; and (2) detecting supporting evidences, i.e. stances, suffers from the difficulty of measuring the similarity between claims and related evidences. We build ClaimVerif, a claim verification system that not only provides credibility assessment for any user-given query claim, but also rationales the assessment results with supporting evidences. ClaimVerif can automatically select the stances from millions of documents and employs two-step training to justify the opinions of the stances. Furthermore, combined with the credibility of stances sources, ClaimVerif degrades the score of stances from untrustworthy sources and alleviates the negative effects from rumor spreaders. Our empirical evaluations show that ClaimVerif achieves both high accuracy and efficiency in different claim verification tasks. It can be highly useful in practical applications by providing multi-dimension analysis for the suspicious statements, including the stances, opinions, source credibility and estimated judgements.
Software metrics : usability and evaluation of software quality
(2008)

It is difficult to understand, let alone improve, the quality of software without the knowledge of its software development process and software products. There must be some measurement process to predict the software development, and to evaluate the software products. This thesis provides a brief view on Software Quality, Software Metrics, and Software Metrics methods that will predict and measure the specified quality factors of software. It further discusses about the Quality as given by the standards such as ISO, principal elements required for the Software Quality and Software Metrics as the measurement technique to predict the Software Quality. This thesis was performed by evaluating a source code developed in Java, using Software Metrics, such as Size Metrics, Complexity Metrics, and Defect Metrics. Results show that, the quality of software can be analyzed, studied and improved by the usage of software metrics.
Learning Embedding Adaptation for Few-Shot Learning
(2018)

Learning with limited data is a key challenge for visual recognition. Few-shot learning methods address this challenge by learning an instance embedding function from seen classes, and apply the function to instances from unseen classes with limited labels. This style of transfer learning is task-agnostic: the embedding function is not learned optimally discriminative with respect to the unseen classes, where discerning among them is the target task. In this paper, we propose a novel approach to adapt the embedding model to the target classification task, yielding embeddings that are task-specific and are discriminative. To this end, we employ a type of self-attention mechanism called Transformer to transform the embeddings from task-agnostic to task-specific by focusing on relating instances from the test instances to the training instances in both seen and unseen classes. Our approach also extends to both transductive and generalized few-shot classification, two important settings that have essential use cases. We verify the effectiveness of our model on two standard benchmark few-shot classification datasets — MiniImageNet and CUB, where our approach demonstrates state-of-the-art empirical performance.
Fabrication of zero-speed sensor using weakly coupled NiFe/CoFe multilayer films
(2004)

A magnetic sensor consisting of NiFe/Al/sub 2/O/sub 3//CoFe thin film was fabricated. Magnetization reversal of the NiFe soft layer was asymmetric in switching to parallel and antiparallel alignments to magnetization of CoFe because of magnetostatic coupling between the NiFe and CoFe layers. When the magnetization of the NiFe was paralleled to that of CoFe, a steep switching accompanied a large Barkhausen jump-induced pulse voltage in a pickup coil as sensor output. Amplitude of the pulse was not dependent on frequency of an external magnetic field. The pulse voltage output was obtained from the sensor element consisting of the optimized film structure excited by the magnetic field at almost zero frequency. These features are also achieved by twisted FeCoV and other wire materials. However, an integrated on-chip sensor with electronic circuits can be fabricated with film-based materials. The film-based sensor elements fabricated in this study can be utilized for speed sensor, rotation sensor, flow meter, and other applications.
Metamaterial-Based Low-Profile Broadband Mushroom Antenna
(2014)

A metamaterial-based broadband low-profile mushroom antenna is presented. The proposed antenna is formed using an array of mushroom cells and a ground plane, and fed by a microstrip line through a slot cut onto the ground plane. With the feeding slot right underneath the center gap between the mushroom cells, the dual resonance modes are excited simultaneously for the radiation at boresight. A transmission-line model integrated with the dispersion relation of a composite right/left-handed mushroom structure is applied to analyze the modes. The proposed dielectric-filled (ε<sub>r</sub>=3.38) mushroom antenna with a low profile of 0.06λ<sub>0</sub> ( λ<sub>0</sub> is the operating wavelength in free space) and a ground plane of 1.10λ<sub>0</sub>×1.10λ<sub>0</sub> attains 25% measured bandwidth with(|S<sub>11</sub>| <; - 10dB) 9.9-dBi average gain at 5-GHz band. Across the bandwidth, the antenna efficiency is greater than 76%, and cross-polarization levels are less than -20 dB.
Integrating shape grammars into a generative system for Zhuang ethnic embroidery design exploration
(2013)

The integration of shape grammars within a generative system is thought to have good potential to support design applications in the art and cultural domains. Based on a shape decomposing method, two-level generative shape grammars are developed within the application of Zhuang ethnic embroidery design. In our approach, free B-spline curves are used to derive initial design concepts together with a new interpolation algorithm. In order to cope with the potentially huge solution space, a novel aesthetic evaluation model and a design exploration algorithm are developed for designers to find their favorite design solutions based on their subjective assessments. A system is introduced to demonstrate this research with an example of Zhuang ethnic embroidery design. © 2012 Elsevier Ltd. All rights reserved.
Foot Design for a Large Walking Delta Robot
(2002)

A large Delta robot has been modified to pick up and place a triangular shaped foot. The robot pushes the foot down to lift the body and the three associated fixed support legs. It then moves the foot sideways so that the body moves in the opposite direction to a new position where the fixed legs are lowered to the ground and the foot lifted ready for a new placement. In this way the robot is able to move in any direction with a tripod gait. The use of a combined foot and gripper for moving heavy objects is investigated. In the implementation reported, the gearboxes used are found to limit the operation and spring assistance is investigated as a trade off with payload. The small prototype, stands as tall as a person, weighs a third of a ton, and has a payload capability of near 100%. It is envisaged as a prototype for a much larger walking robot capable of general-purpose heavy lifting.
From a Set of Shapes to Object Discovery
(2010)

This paper presents an approach to object discovery in a give n unlabeled image set, based on mining repetitive spatial config urations of image contours. Contours that similarly deform from one image to a n ther are viewed as collaborating, or, otherwise, conflicting. This is captu red by a graph over all pairs of matching contours, whose maximum a posteriori mult icoloring assignment is taken to represent the shapes of discovered objects. Multicoloring is conducted by our new Coordinate Ascent Swendsen-Wang cut (CASW ). CASW uses the Metropolis-Hastings (MH) reversible jumps to probabil istically sample graph edges, and color nodes. CASW extends SW cut by introducing a r e ularization in the posterior of multicoloring assignments that prevent s the MH jumps to arrive at trivial solutions. Also, CASW seeks to learn paramet ers of the posterior via maximizing a lower bound of the MH acceptance rate. This s peeds up multicoloring iterations, and facilitates MH jumps from local mi nima. On benchmark datasets, we outperform all existing approaches to unsuper vised object discovery.
Person Re-identification by Discriminatively Selecting Parts and Features
(2014)

This paper presents a novel appearance-based method for person re-identification. The core idea is to rank and select different body parts on the basis of the discriminating power of their characteristic features. In our approach, we first segment the pedestrian images into meaningful parts, then we extract features from such parts as well as from the whole body and finally, we perform a salience analysis based on regression coefficients. Given a set of individuals, our method is able to estimate the different importance (or salience) of each body part automatically. To prove the effectiveness of our approach, we considered two standard datasets and we demonstrated through an exhaustive experimental section how our method improves significantly upon existing approaches, especially in multiple-shot scenarios.
A Pipelined CRC Calculation Using Lookup Tables
(2010)

We present a fast cyclic redundancy check (CRC) algorithm that performs CRC computation for any length of message in parallel. Traditional CRC implementations have feedbacks, which make pipelining problematic. In the proposed approach, we eliminate feedbacks and implement a pipelined calculation of 32-bit CRC in the SMIC 0.13 μm CMOS technology. For a given message, the algorithm first chunks the message into blocks, each of which has a fixed size equal to the degree of the generator polynomial. Then it computes CRC for the chunked blocks in parallel using lookup tables, and the results are combined together by performing XOR operations. The simulation results show that our proposed pipelined CRC is more efficient than existing CRC implementations.
Periodic Leaky-Wave Antenna Array With Horizontally Polarized Omnidirectional Pattern
(2012)

A novel periodic leaky-wave antenna for broadside radiation with horizontally polarized omnidirectional pattern is proposed, designed and demonstrated experimentally. The objective is to achieve a horizontally polarized omnidirectional antenna array with highly directive beam. The proposed structure is based on combining the rotating electric field method and a leaky-wave antenna design. By properly designing a unit cell with a pair of crossed dipoles spaced at a distance approximately equal to λg/4 at the center frequency, not only omnidirectional radiation pattern with horizontal polarization is obtained by crossed dipoles fed in phase quadrature, but also the open-stopband effect exhibited at broadside scan is significantly reduced. The analysis and design of this structure are performed on the basis of a simple equivalent network model. A finite structure formed by 16-unit cell (32-element) for broadside beam is developed at the 2.4 GHz band, which offers a horizontally polarized omnidirectional radiation pattern with enhanced gain of 9.9-10.6 dBi and measured radiation efficiency of 90% for the covering bands.
A comprehensive study of visual event computing
(2010)

This paper contains a survey on aspects of visual event computing. We start by presenting events and their classifications, and continue with discussing the problem of capturing events in terms of photographs, videos, etc, as well as the methodologies for event storing and retrieving. Later, we review an extensive set of papers taken from well-known conferences and journals in multiple disciplines. We analyze events, and summarize the procedure of visual event actions. We introduce each component of a visual event computing system, and its computational aspects, we discuss the progress of each component and review its overall status. Finally, we suggest future research trends in event computing and hope to introduce a comprehensive profile of visual event computing to readers.
Estimation of safe sensor measurements of autonomous system under attack
(2017)

The introduction of automation in cyber-physical systems (CPS) has raised major safety and security concerns. One attack vector is the sensing unit whose measurements can be manipulated by an adversary through attacks such as denial of service and delay injection. To secure an autonomous CPS from such attacks, we use a challenge response authentication (CRA) technique for detection of attack in active sensors data and estimate safe measurements using the recursive least square algorithm. For demonstrating effectiveness of our proposed approach, a car-follower model is considered where the follower vehicle's radar sensor measurements are manipulated in an attempt to cause a collision.
How robust are prediction effects in language comprehension? Failure to replicate article-elicited N400 effects
(2017)

Current psycholinguistic theory proffers prediction as a central, explanatory mechanism in language processing. However, widely-replicated prediction effects may not mean that prediction is necessary in language processing. As a case in point, C. D. Martin et al. [2013. Bilinguals reading in their second language do not predict upcoming words as native readers do. Journal of Memory and Language, 69(4), 574–588. doi:10.1016/j.jml.2013.08.001] reported ERP evidence for prediction in nativebut not in non-native speakers. Articles mismatching an expected noun elicited larger negativity in the N400 time window compared to articles matching the expected noun in native speakers only. We attempted to replicate these findings, but found no evidence for prediction irrespective of language nativeness. We argue that pre-activation of phonological form of upcoming nouns, as evidenced in article-elicited effects, may not be a robust phenomenon. A view of prediction as a necessary computation in language comprehension must be re-evaluated. ARTICLE HISTORY Received 1 June 2016 Accepted 22 September 2016
Filterbank-based fingerprint matching
(2000)

With identity fraud in our society reaching unprecedented proportions and with an increasing emphasis on the emerging automatic personal identification applications, biometrics-based verification, especially fingerprint-based identification, is receiving a lot of attention. There are two major shortcomings of the traditional approaches to fingerprint representation. For a considerable fraction of population, the representations based on explicit detection of complete ridge structures in the fingerprint are difficult to extract automatically. The widely used minutiae-based representation does not utilize a significant component of the rich discriminatory information available in the fingerprints. Local ridge structures cannot be completely characterized by minutiae. Further, minutiae-based matching has difficulty in quickly matching two fingerprint images containing a different number of unregistered minutiae points. The proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature. Our system performs better than a state-of-the-art minutiae-based system when the performance requirement of the application system does not demand a very low false acceptance rate. Finally, we show that the matching performance can be improved by combining the decisions of the matchers based on complementary (minutiae-based and filter-based) fingerprint information.
On-line fingerprint verification
(1996)

Fingerprint verification is one of the most reliable personal identification methods. However, manual fingerprint verification is so tedious, time-consuming, and expensive that it is incapable of meeting today’s increasing performance requirements. An automatic fingerprint identification system (AFIS) is widely needed. It plays a very important role in forensic and civilian applications such as criminal identification, access control, and ATM card verification. This paper describes the design and implementation of an on-line fingerprint verification system which operates in two stages: minutia extraction and minutia matching. An improved version of the minutia extraction algorithm proposed by Ratha et al., which is much faster and more reliable, is implemented for extracting features from an input fingerprint image captured with an on-line inkless scanner. For minutia matching, an alignment-based elastic matching algorithm has been developed. This algorithm is capable of finding the correspondences between minutiae in the input image and the stored template without resorting to exhaustive search and has the ability of adaptively compensating for the nonlinear deformations and inexact pose transformations between fingerprints. The system has been tested on two sets of fingerprint images captured with inkless scanners. The verification accuracy is found to be acceptable. Typically, a complete fingerprint verification procedure takes, on an average, about eight seconds on a SPARC 20 workstation. These experimental results show that our system meets the response time requirements of on-line verification with high accuracy. Index Terms —Biometrics, fingerprints, matching, verification, minutia, orientation field, ridge extraction. —————————— ✦ ——————————
FVC2002: Second Fingerprint Verification Competition
(2002)

Two years after the first edition, a new Fingerprint Verification Competition (FVC2002) was organized by the authors, with the aim of determining the state-of-theart in this challenging pattern recognition application. The experience and the feedback received from FVC2000 allowed the authors to improve the organization of FVC2002 and to capture the attention of a significantly higher number of academic and commercial organizations (33 algorithms were submitted). This paper discusses the FVC2002 database, the test protocol and the main differences between FVC2000 and FVC2002. The algorithm performance evaluation will be presented at the 16 ICPR.
Cover your ACKs: pitfalls of covert channel censorship circumvention
(2013)

In response to increasingly sophisticated methods of blocking access to censorship circumvention schemes such as Tor, recently proposed systems such as Skypemorph, FreeWave, and CensorSpoofer have used voice and video conferencing protocols as "cover channels" to hide proxy connections. We demonstrate that even with perfect emulation of the cover channel, these systems can be vulnerable to attacks that detect or disrupt the covert communications while having no effect on legitimate cover traffic. Our attacks stem from differences in the channel requirements for the cover protocols, which are peer-to-peer and loss tolerant, and the covert traffic, which is client-proxy and loss intolerant. These differences represent significant limitations and suggest that such protocols are a poor choice of cover channel for general censorship circumvention schemes.
Smart Agents in Industrial Cyber–Physical Systems
(2016)

Future industrial systems can be realized using the cyber-physical systems (CPSs) that advocate the coexistence of cyber and physical counterparts in a network structure to perform the system's functions in a collaborative manner. Multiagent systems share common ground with CPSs and can empower them with a multitude of capabilities in their efforts to achieve complexity management, decentralization, intelligence, modularity, flexibility, robustness, adaptation, and responsiveness. This work surveys and analyzes the current state of the industrial application of agent technology in CPSs, and provides a vision on the way agents can effectively enable emerging CPS challenges.